code: def parse_val_archive(
      root: str,
      file: Optional[str] = None,
      wnids: Optional[List[str]] = None,
      folder: str = "val",
  ) -> None:
      """Parse the validation images archive of the ImageNet2012 classification dataset
      and prepare it for usage with the ImageNet dataset.
  
      Args:
          root (str): Root directory containing the validation images archive
          file (str, optional): Name of validation images archive. Defaults to
              'ILSVRC2012_img_val.tar'
          wnids (list, optional): List of WordNet IDs of the validation images. If None
              is given, the IDs are loaded from the meta file in the root directory
          folder (str, optional): Optional name for validation images folder. Defaults to
              'val'
      """
      archive_meta = ARCHIVE_META["val"]
      if file is None:
          file = archive_meta[0]
      md5 = archive_meta[1]
      if wnids is None:
          wnids = load_meta_file(root)[1]
  
      _verify_archive(root, file, md5)
  
      val_root = os.path.join(root, folder)
      extract_archive(os.path.join(root, file), val_root)
  
      images = sorted(
          os.path.join(val_root, image)
          for image in os.listdir(val_root)
      )
  
      for wnid in set(wnids):
          os.mkdir(os.path.join(val_root, wnid))
  
      for wnid, img_file in zip(wnids, images):
          shutil.move(
              img_file,
              os.path.join(val_root, wnid, os.path.basename(img_file)),
          )
  
file_path: vision/torchvision/datasets/imagenet.py
imports: import os
  import shutil
  import tempfile
  from contextlib import contextmanager
  from typing import Any, Dict, Iterator, List, Optional, Tuple
  import torch
  from .folder import ImageFolder
  from .utils import check_integrity, extract_archive, verify_str_arg
label_desc: Use image node_id 5 for calling a global function with example usage: parse_val_archive(root, file, wnids, folder) without return types